ABSTRACT
The mental lexicon contains the knowledge about words acquired over a lifetime. A
central question is how this knowledge is structured and changes over time. Here we
propose to represent this lexicon as a network consisting of nodes that correspond
to words and links reflecting associative relations between two nodes, based on free
association data. A network view of the mental lexicon is inherent to many cognitive
theories, but the predictions of a working model strongly depend on a realistic scale,
with recent methods from network science allows us to answer questions about its
organization at different scales simultaneously, such as: How efficient and robust is
are the organization principles of words in the mental lexicon (i.e. thematic versus
taxonomic)? How does the local connectivity with neighboring words explain why
certain words are processed more efficiently than others? Networks built from word
such as developmental shifts, individual differences in creativity, or clinical states like
schizophrenia. While these phenomena can be studied using these networks, various
future challenges and ways in which this proposal complements other perspectives
are also discussed.
